Disaster information processing apparatus, operation method of disaster information processing apparatus, operation program of disaster information processing apparatus, and disaster information processing system

ABSTRACT

Provided are a disaster information processing apparatus, an operation method of a disaster information processing apparatus, an operation program of a disaster information processing apparatus, and a disaster information processing system capable of grasping a damage situation at a disaster site in a short time without waste. A RW control unit receives a first aerial image obtained by capturing a first imaging range including an area by a first camera mounted on a first drone. A first damage situation analysis unit analyzes a first damage situation of a disaster in the first imaging range based on the first aerial image. A second imaging range determination unit determines a second imaging range of a second camera mounted on a second drone based on a first analysis result, and the second imaging range is relatively narrower than the first imaging range.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation application of InternationalApplication No. PCT/JP2021/032903 filed on Sep. 7, 2021, the disclosureof which is incorporated herein by reference in its entirety. Further,this application claims priority from Japanese Patent Application No.2020-167014 filed on Oct. 1, 2020, the disclosure of which isincorporated herein by reference in its entirety.

BACKGROUND 1. Technical Field

The disclosed technology relates to a disaster information processingapparatus, an operation method of a disaster information processingapparatus, an operation program of a disaster information processingapparatus, and a disaster information processing system.

2. Description of the Related Art

Various disasters such as earthquakes, tsunamis, volcanic eruptions,floods and/or landslides caused by heavy rains, and large-scale fireshave been occurring in various places. In the related art, variouscountermeasures for grasping a damage situation of such a disaster havebeen proposed. For example, JP2013-134663A describes a disasterinformation processing apparatus that sends a drone to a disaster site,causes a camera mounted on the drone to capture the disaster site, andgrasps a damage situation at the disaster site based on an aerial imageobtained in this manner. The disaster site is, for example, a mainbuilding in a disaster-stricken area where fire is occurring, a mainbuilding in a disaster-stricken area inundated by a flood, and the like.

SUMMARY

In JP2013-134663A, the discussion proceeds on the assumption that thedisaster site is known to some extent. However, although a roughdisaster-stricken area including the disaster site can be knownimmediately after the occurrence of a disaster, it is not clear wherethe disaster site is in the disaster-stricken area is the disaster sitedue to confusion peculiar to the disaster such as destruction of aninformation transmission infrastructure such as a mobile phone basestation in many cases.

In a situation where it is not clear where the disaster site is in thedisaster-stricken area, for example, it is considered that the damagesituation at the disaster site is grasped with one drone. In this case,since it is necessary to thoroughly explore the disaster-stricken areawith one drone, it can be easily imagined that it will take a very longtime.

In contrast, it is considered that the damage situation at the disastersite is grasped with a plurality of drones. In this case, in a casewhere the disaster-stricken area is shared and explored by the pluralityof drones, a time can be shortened as compared with the case of onedrone. However, simply flying the plurality of drones without any goalis wasteful.

One embodiment according to the disclosed technology provides a disasterinformation processing apparatus, an operation method of a disasterinformation processing apparatus, an operation program of a disasterinformation processing apparatus, and a disaster information processingsystem capable of grasping a damage situation at a disaster site in ashort time without waste.

A disaster information processing apparatus of the present disclosurecomprises a processor, and a memory connected to or built in theprocessor. The processor is configured to receive a first aerial imageobtained by capturing a first imaging range including adisaster-stricken area by a first camera mounted on a first drone,analyze a first damage situation of a disaster in the first imagingrange based on the first aerial image, and determine a second imagingrange of a second camera mounted on a second drone based on an analysisresult of the first damage situation, the second imaging range beingrelatively narrower than the first imaging range.

It is preferable that the processor is configured to determine, as thesecond imaging range, an imaging range including a region where damageis determined to be relatively large as a result of the analysis of thefirst damage situation in the disaster-stricken area.

It is preferable that the processor is configured to receive a secondaerial image obtained by capturing the second imaging range by thesecond camera, and analyze a second damage situation of the disaster inthe second imaging range based on the second aerial image.

It is preferable that the processor is configured to analyze the seconddamage situation based on the first aerial image in addition to thesecond aerial image.

It is preferable that the processor is configured to set flight altitudeof the second drone to be lower than flight altitude of the first drone.

It is preferable that the processor is configured to analyze the firstdamage situation for each compartment including a plurality of adjacentbuildings.

It is preferable that a flight range is set for the second drone inadvance, and the processor is configured to determine, as the secondimaging range of a target second drone, an imaging range including aregion where damage is determined to be relatively large in a case wheredamage of a region within the flight range of the target second drone isdetermined to be relatively small and there is a region where damage isdetermined to be relatively large in a flight range different from theflight range of the target second drone as a result of the analysis ofthe first damage situation.

It is preferable that a plurality of the second drones are provided, andthe processor is configured to determine the second imaging range foreach of the plurality of second drones.

An operation method of a disaster information processing apparatus ofthe present disclosure comprises receiving a first aerial image obtainedby capturing a first imaging range including a disaster-stricken area bya first camera mounted on a first drone, analyzing a first damagesituation of a disaster in the first imaging range based on the firstaerial image, and determining a second imaging range of a second cameramounted on a second drone based on an analysis result of the firstdamage situation, the second imaging range being relatively narrowerthan the first imaging range.

An operation program of a disaster information processing apparatus ofthe present disclosure causes a computer to execute processing ofreceiving a first aerial image obtained by capturing a first imagingrange including a disaster-stricken area by a first camera mounted on afirst drone, analyzing a first damage situation of a disaster in thefirst imaging range based on the first aerial image, and determining asecond imaging range of a second camera mounted on a second drone basedon an analysis result of the first damage situation, the second imagingrange being relatively narrower than the first imaging range.

A disaster information processing system of the present disclosurecomprises a first drone on which a first camera that captures a firstimaging range including a disaster-stricken area to output a firstaerial image is mounted, a second drone on which a second camera thatcaptures a second imaging range relatively narrower than the firstimaging range to output a second aerial image is mounted, a processor,and a memory connected to or built in the processor. The processor isconfigured to receive the first aerial image, analyze a first damagesituation of a disaster in the first imaging range based on the firstaerial image, and determine the second imaging range based on ananalysis result of the first damage situation.

According to the disclosed technology, it is possible to provide thedisaster information processing apparatus, the operation method of adisaster information processing apparatus, the operation program of adisaster information processing apparatus, and the disaster informationprocessing system capable of grasping the damage situation at thedisaster site in a short time without waste.

BRIEF DESCRIPTION OF THE DRAWINGS

Exemplary embodiments according to the technique of the presentdisclosure will be described in detail based on the following figures,wherein:

FIG. 1 is a diagram showing a disaster information processing system;

FIG. 2 is a diagram showing a relationship between an area and a flightrange;

FIG. 3 is a diagram showing flight altitudes of a first drone and asecond drone;

FIG. 4 is a diagram showing the first drone or the second drone;

FIG. 5 is a block diagram of the first drone or the second drone;

FIG. 6 is a diagram showing first imaging range information;

FIG. 7 is a diagram showing a relationship between a flight range and afirst imaging range;

FIG. 8 is a block diagram showing a computer constituting a disasterinformation processing server;

FIG. 9 is a block diagram showing a processing unit of a CPU of thedisaster information processing server;

FIG. 10 is a block diagram showing details of a first damage situationanalysis unit;

FIG. 11 is a diagram showing an outline of processing in a trainingphase of a first damage situation analysis model;

FIG. 12 is a diagram showing processing of a second imaging rangedetermination unit;

FIG. 13 is a diagram showing a relationship between a compartment and asecond imaging range;

FIG. 14 is a block diagram showing details of a second damage situationanalysis unit;

FIG. 15 is a diagram showing an outline of processing in a trainingphase of a second damage situation analysis model;

FIG. 16 is a diagram showing a damage situation display screen;

FIG. 17 is a diagram showing a processing procedure of the disasterinformation processing server;

FIG. 18 is a diagram showing the processing procedure of the disasterinformation processing server;

FIG. 19 is a block diagram showing details of a second damage situationanalysis unit of a second embodiment;

FIG. 20 is a diagram showing an outline of processing in a trainingphase of a second damage situation analysis model of the secondembodiment; and

FIG. 21 is a diagram showing a third embodiment in which a second droneis sent to support a region where damage in another flight range isdetermined to be relatively large.

DETAILED DESCRIPTION First Embodiment

As an example, as shown in FIG. 1 , a disaster information processingsystem 2 for grasping a damage situation of a disaster comprises firstdrones 10_1, 10_2, and 10_3, second drones 11A_1, 11B_1, 11A_2, 11B_2,11A_3, and 11B_3, and a disaster information processing server 12. Thefirst drones 10_1, 10_2, and 10_3 and the second drones 11A_1, 11B_1,11A_2, 11B_2, 11A_3, and 11B_3 are identical models and have the sameperformance. Hereinafter, in a case where it is not necessary todistinguish between the first drones 10_1, 10_2, and 10_3, the firstdrones are collectively referred to as the first drones 10. Similarly,the second drones 11A_1, 11B_1, 11A_2, 11B_2, 11A_3, and 11B_3 arecollectively referred to as the second drones 11. Underbars may besimilarly omitted for reference numerals having other underbars (such asFR_1, FR_2, and FR_3, FB_1, FB_2, and FB_3, 80_N, 80_E, 80_S, and 80_W).

The first drone 10_1 and the second drones 11A_1 and 11B_1 are in chargeof a first flight range FR_1. The first drone 10_2 and the second drones11A_2 and 11B_2 are in charge of a second flight range FR_2. The firstdrone 10_3 and the second drones 11A_3 and 11B_3 are in charge of athird flight range FR_3. As described above, the flight ranges FR areset for the first drones 10 and the second drones 11 in advance.

The first drones 10, the second drones 11, and the disaster informationprocessing server 12 are connected to each other via a network 13 to becommunicable with each other. The first drones 10 and the second drones11 are wirelessly connected to the network 13. The disaster informationprocessing server 12 is connected to the network 13 in a wired orwireless manner. The network 13 is a wide area network (WAN) of, forexample, the Internet, a public communication network, or the like. In acase where WAN is used, it is preferable to construct a virtual privatenetwork (VPN) or to use a communication protocol having a high securitylevel such as Hypertext Transform Protocol Secure (HTTPS) inconsideration of information security.

The disaster information processing server 12 is installed at, forexample, a disaster response headquarters (agency, government office, orthe like) of a local government such as a prefecture or a municipality.The disaster information processing server 12 is an example of a“disaster information processing apparatus” according to the disclosedtechnology.

A client terminal 14 is also connected to the network 13 in a wired orwireless manner. The client terminal 14 is, for example, a desktoppersonal computer owned by a staff member of the disaster responseheadquarters and has a display 15 and an input device 16. Variousscreens are displayed on the display 15. The input device 16 is akeyboard, a mouse, a touch panel, a microphone, or the like. Althoughonly one client terminal 14 is drawn in FIG. 1 , of course, a pluralityof client terminals 14 may be provided.

As shown in FIG. 2 in which an area 20 such as a prefecture or amunicipality is viewed from above, the flight ranges FR are, forexample, circles with a radius of 5 km to 10 km, and are set in advanceto cover the entire area 20. The flight ranges FR may partially overlapas shown in the drawing. The flight range FR has a departure and arrivalbase FB of the first drone 10 and the second drone 11 at a centerthereof. More specifically, the first flight range FR_1 has a firstdeparture and arrival base FB_1, a second flight range FR_2 has a seconddeparture and arrival base FB_2, and a third flight range FR_3 has athird departure and arrival base FB_3. The area 20 is an area where thedisaster response headquarters is located due to the disaster, and is anexample of a “disaster-stricken area” according to the disclosedtechnology.

As an example, as shown in FIG. 3 , the first drone 10 takes off fromthe departure and arrival base FB prior to the second drone 11, andcaptures a first aerial image 25 from, for example, a flight altitude of500 m. After the first aerial image 25 is captured, the first drone 10returns to the departure and arrival base FB. In contrast, the seconddrone 11 takes off from the departure and arrival base FB after thefirst drone 10, and captures a second aerial image 26 from, for example,a flight altitude of 100 m. After the second aerial image 26 iscaptured, the second drone 11 returns to the departure and arrival baseFB. The first drone 10 and the second drone 11 capture the first aerialimage 25 and the second aerial image 26 by setting a zoom magnificationto the same value, for example, 1×. Thus, relatively many buildingsappear relatively small in the first aerial image 25. In contrast, inthe second aerial image 26, relatively few buildings appear relativelylarge.

As an example, as shown in FIG. 4 , the first drone 10 or the seconddrone 11 includes an airframe 30, arms 31, propellers 32, motors 33,skids 34, a gimbal 35, a first camera 36 or a second camera 37, and thelike. The first camera 36 is mounted on the first drone 10, and thesecond camera 37 is mounted on the second drone 11. The propellers 32are also called blades or rotary wings. The motors 33 are also calledrotors.

The arms 31 are four rod-like bodies extending from the airframe 30 infour directions symmetrical in a lateral direction. A total of fourpropellers 32 are provided at tip parts of the arms 31 one by one. Themotor 33 is attached to the propeller 32. The motor 33 rotates thepropeller 32 to fly the first drone 10 or the second drone 11. The motor33 changes a flight direction of the first drone 10 or the second drone11 by changing a rotation direction and a rotation speed thereof.

The skids 34 are four rod-like bodies extending from the airframe 30 infour directions symmetrical in a downward direction. The skids 34 areprovided to allow the first drone 10 or the second drone 11 to stablyland on the ground. The gimbal 35 holds the first camera 36 or thesecond camera 37 in a tiltable manner at a lower part of the airframe30. The gimbal 35 reduces shaking generated in the airframe 30 duringflight not to be transmitted to the first camera 36 or the second camera37.

As an example, as shown in FIG. 5 , the first drone 10 or the seconddrone 11 includes a storage 40, a memory 41, a central processing unit(CPU) 42, a communication unit 43, a power feed unit 44, and the like.

The memory 41 is a work memory for the CPU 42 to execute processing. TheCPU 42 loads an operation program 45 stored in the storage 40 into thememory 41 and executes processing corresponding to the operation program45. Accordingly, the CPU 42 comprehensively controls an operation ofeach unit of the first drone 10 or the second drone 11.

The communication unit 43 is responsible for wireless communication withthe disaster information processing server 12 and a piloted aircraft 50.The piloted aircraft 50 is operated by an operator of the first drone 10or the second drone 11. The first drone 10 or the second drone 11 isbasically an autonomous flight, but can be manually operated by thepiloted aircraft 50 in order to respond to an emergency. The pilotedaircraft 50 is also referred to as a proportional system, or a radio forshort.

A rechargeable battery 53 such as a secondary battery is connected tothe power feed unit 44. The power feed unit 44 feeds power from thebattery 53 to each unit.

A Global Positioning System (GPS) module 55, a gyro sensor 56, anacceleration sensor 57, an azimuth sensor 58, an altitude sensor 59, andthe like are connected to the CPU 42.

The GPS module 55 receives a signal from a GPS satellite and specifieslongitude and latitude of a position of the first drone 10 or the seconddrone 11 based on the received signal. The GPS module 55 outputs thespecified longitude and latitude to the CPU 42.

The gyro sensor 56 detects an inclination angle representing a pose ofthe first drone 10 or the second drone 11. The gyro sensor 56 outputsthe detected inclination angle to the CPU 42. The acceleration sensor 57detects an acceleration of the first drone 10 or the second drone 11.The acceleration sensor 57 outputs the detected acceleration to the CPU42. A speed of the first drone 10 or the second drone 11 may becalculated by integrating the acceleration detected by the accelerationsensor 57.

The azimuth sensor 58 detects an angle representing azimuth in which afront surface of the first drone 10 or the second drone 11 faces, thatis, an azimuthal angle, based on geomagnetism. The azimuth sensor 58outputs the detected azimuthal angle to the CPU 42. The front surface ofthe first drone 10 or the second drone 11 is a side on which a lensoptical axis of the first camera 36 or the second camera 37 faces.

The altitude sensor 59 detects the flight altitude of the first drone 10or the second drone 11. The altitude sensor 59 is, for example, a sensorthat measures an air pressure and converts the air pressure into flightaltitude. The altitude sensor 59 may be a sensor that irradiates aground surface with an infrared laser beam, receives reflected lightthereof, and measures a distance from the ground surface based on thereceived reflected light. Alternatively, the altitude sensor 59 may bean ultrasound sensor that irradiates the ground surface with ultrasonicwaves, receives an echo thereof, and measures a distance from the groundsurface based on the received echo. The altitude sensor 59 outputs thedetected flight altitude to the CPU 42.

In a case where the first drone 10 or the second drone 11 is powered onto activate the operation program 45, the CPU 42 functions as a flightcontroller 65 and a camera controller 66. The flight controller 65controls an operation of the motor 33 via a motor driver 67. The cameracontroller 66 controls an operation of the first camera 36 or the secondcamera 37 to cause the first camera 36 to capture the first aerial image25 and the second camera 37 to capture the second aerial image 26. Thecamera controller 66 receives the first aerial image 25 or the secondaerial image 26 from the first camera 36 or the second camera 37,performs image processing on the first aerial image 25 or the secondaerial image 26, and then transmits the first aerial image 25 or thesecond aerial image 26 to the disaster information processing server 12via the communication unit 43.

The storage 40 stores a first imaging range information 70 or a secondimaging range information 71. More specifically, the storage 40 of thefirst drone 10 stores the first imaging range information 70, and thestorage 40 of the second drone 11 stores the second imaging rangeinformation 71. The first imaging range information 70 is stored in thestorage 40 of the first drone 10 in advance before the occurrence of thedisaster. In contrast, the second imaging range information 71 istransmitted from the disaster information processing server 12 to thesecond drone 11 after the occurrence of the disaster, and is stored inthe storage 40 of the second drone 11. The flight controller 65 performscontrol corresponding to the first imaging range information 70 or thesecond imaging range information 71 while referring to various kinds ofinput data from the GPS module 55, the gyro sensor 56, the accelerationsensor 57, the azimuth sensor 58, the altitude sensor 59, and the like.

As an example, as shown in FIG. 6 , the first imaging range information70 is information on a first imaging range 80 (see FIG. 7 ) which is animaging range of the first aerial image 25 of the first camera 36.Specifically, the first imaging range information 70 includes items oflongitude and latitude, azimuth, and altitude. For example, longitudeand latitude in the sky above the departure and arrival base FB isregistered in the item of latitude and longitude. For example, fourazimuthal angles of 0° (north), 90° (east), 180° (south), and 270°(west) are registered in the item of azimuth. For example, 500 m shownin FIG. 3 is registered as the item of altitude.

As an example, as shown in FIG. 7 , the first imaging range 80 definedby the first imaging range information 70 has a rectangular shape andhas four first imaging ranges 80_N, 80_E, 80_S, and 80_W. The firstimaging ranges 80_N, 80_E, 80_S, and 80_W cover the entire flight rangeFR. The first imaging range 80_N is an imaging range in a case where theazimuthal angle of the first drone 10 is 0°. Similarly, the firstimaging range 80_E is an imaging range in a case where the azimuthalangle of the first drone 10 is 90°, the first imaging range 80_S is animaging range in a case where the azimuthal angle of the first drone 10is 180°, and the first imaging range 80_W is an imaging range in a casewhere the azimuthal angle of the first drone 10 is 270°. All of thefirst imaging ranges 80_N, 80_E, 80_S, and 80_W are imaging ranges in acase where the departure and arrival base FB is viewed directly below bythe first camera 36.

The flight controller 65 of the first drone 10 first causes the firstdrone 10 to fly to a position 500 m above the departure and arrival baseFB according to the first imaging range information 70. The azimuthalangles are sequentially changed to 0°, 90°, 180°, and 270° while thefirst drone 10 is hovered at a position 500 m above the departure andarrival base FB. The camera controller 66 of the first drone 10 capturesthe first imaging ranges 80_N, 80_E, 80_S, and 80_W at the azimuthalangles of 0°, 90°, 180°, and 270°, and captures a total of four firstaerial images 25.

A range in which damage situations of buildings appearing in the firstaerial image 25 can be analyzed is set as the first imaging range 80.The first imaging range 80 varies according to the flight altitude ofthe first drone 10, a resolution of the first camera 36, an angle ofview of the first camera 36, and the like. Thus, there are cases wherethe entire flight range FR is covered by the plurality of first imagingranges 80 as in the example of FIG. 7 , and there are cases where theentire flight range FR can be covered by one first imaging range 80.

As an example, as shown in FIG. 8 , a computer constituting the disasterinformation processing server 12 comprises a storage 85, a memory 86, acentral processing unit (CPU) 87, and a communication unit 88. Thesecomponents are interconnected via a busline 89. The CPU 87 is an exampleof a “processor” according to the disclosed technology.

The storage 85 is a hard disk drive built in the computer constitutingthe disaster information processing server 12 or connected via a cableor the network 13. Alternatively, the storage 85 is a disk array inwhich a plurality of hard disk drives are connected in series. Thestorage 85 stores a control program such as an operating system, variousapplication programs, various kinds of data associated with theseprograms, and the like. A solid state drive may be used instead of thehard disk drive.

The memory 86 is a work memory for the CPU 87 to execute processing. TheCPU 87 loads the program stored in the storage 85 into the memory 86 andexecutes processing corresponding to the program. Accordingly, the CPU87 comprehensively controls an operation of each unit of the computer.The communication unit 88 performs transmission control of various kindsof information to external devices such as the first drone 10 and thesecond drone 11. The memory 86 may be built in the CPU 87.

As an example, as shown in FIG. 9 , an operation program 95 is stored inthe storage 85 of the disaster information processing server 12. Theoperation program 95 is an application program for causing the computerto function as the disaster information processing server 12. That is,the operation program 95 is an example of an “operation program of adisaster information processing apparatus” according to the disclosedtechnology.

In a case where the operation program 95 is started, the CPU 87 of thecomputer constituting the disaster information processing server 12functions as a read and write (hereinafter, abbreviated as RW) controlunit 100, a first damage situation analysis unit 101, a second imagingrange determination unit 102, a transmission control unit 103, a seconddamage situation analysis unit 104, and a screen distribution controlunit 105 in cooperation with the memory 86 and the like.

The RW control unit 100 controls the storage of various kinds of data inthe storage 85 and the reading-out of various kinds of data in thestorage 85. For example, the RW control unit 100 receives the firstaerial image 25 from the first drone 10 and stores the received firstaerial image 25 in the storage 85. The RW control unit 100 receives thesecond aerial image 26 from the second drone 11 and stores the receivedsecond aerial image 26 in the storage 85.

The RW control unit 100 reads out the first aerial image 25 from thestorage 85 and outputs the read-out first aerial image 25 to the firstdamage situation analysis unit 101. The RW control unit 100 reads outthe second aerial image 26 from the storage 85 and outputs the read-outsecond aerial image 26 to the second damage situation analysis unit 104.

The first damage situation analysis unit 101 analyzes a first damagesituation 127 (see FIG. 10 ) of the disaster in the first imaging range80 based on the first aerial image 25. The first damage situationanalysis unit 101 outputs an analysis result (hereinafter, abbreviatedas a first analysis result) 110 of the first damage situation 127 to thesecond imaging range determination unit 102.

The second imaging range determination unit 102 determines a secondimaging range 136 (see FIG. 13 ) of the second camera 37 of the seconddrone 11 based on the first analysis result 110. The second imagingrange determination unit 102 outputs the second imaging rangeinformation 71 which is information on the determined second imagingrange 136 to the transmission control unit 103. The transmission controlunit 103 performs control such that the second imaging range information71 is transmitted to the second drone 11.

The second damage situation analysis unit 104 analyzes a second damagesituation 148 (see FIG. 14 ) of the disaster in the second imaging range136 based on the second aerial image 26. The second damage situationanalysis unit 104 outputs an analysis result (hereinafter, abbreviatedas a second analysis result) 111 of the second damage situation 148 tothe RW control unit 100. The RW control unit 100 stores the secondanalysis result 111 in the storage 85.

In a case where a distribution request (not shown) from the clientterminal 14 is received, the RW control unit 100 reads out the secondanalysis result 111 from the storage 85 and outputs the read-out secondanalysis result 111 to the screen distribution control unit 105. Thescreen distribution control unit 105 generates a damage situationdisplay screen 112 based on the second analysis result 111. The screendistribution control unit 105 performs control such that screen data ofthe generated damage situation display screen 112 is distributed to theclient terminal 14 that is a request source of the distribution request.The screen data is, for example, screen data for web distributioncreated by a markup language such as Extensible Markup Language (XML).The client terminal 14 reproduces and displays the damage situationdisplay screen 112 on a web browser based on the screen data. Anotherdata description language such as JSON (Javascript (registeredtrademark) Object Notation) may be used instead of XML.

As an example, as shown in FIG. 10 , the first damage situation analysisunit 101 includes a compartment image cutout unit 120 and a firstprocessing unit 121. The compartment image cutout unit 120 cuts out acompartment image 123 for each compartment 135 (see FIG. 13 ) from thefirst aerial image 25 while referring to landmark building information122. The compartment 135 is a plurality of regions obtained by dividingthe area 20, and is a region including a plurality of adjacentbuildings. In the present example, the compartment 135 is a chome suchas “Fuji 1-chome” or “Watabukitsuneana 2-chome”. The compartment imagecutout unit 120 outputs a compartment image group 125 including aplurality of sets of the compartment image 123 and compartmentinformation 124 representing the compartment 135 of the compartmentimage 123 to the first processing unit 121.

The landmark building information 122 is stored in the storage 85, isread out from the storage 85 by the RW control unit 100, and is outputto the compartment image cutout unit 120. The landmark buildinginformation 122 includes aerial images of landmark buildings which arebuildings positioned at a corner of each compartment 135, and thecompartment information 124 of the compartment 135 to which the landmarkbuildings belong. The compartment image cutout unit 120 finds thelandmark building from the first aerial image 25 by using a well-knownimage recognition technology and relying on the aerial images of thelandmark buildings. A region surrounded by a line connecting the foundlandmark buildings is cut out as the compartment image 123 from thefirst aerial image 25.

The first processing unit 121 inputs the compartment image 123 into afirst damage situation analysis model 126. The first damage situation127 is output from the first damage situation analysis model 126. Thefirst damage situation 127 is any one of “large damage” or “smalldamage”. The first processing unit 121 outputs the first damagesituation 127 from the first damage situation analysis model 126 for allthe compartment images 123 included in the compartment image group 125.The first processing unit 121 outputs a first analysis result 110 inwhich the first damage situation 127 for each compartment 135 issummarized. FIG. 10 illustrates a case where the first damage situations127 of the compartments 135 such as “Fuji 1-chome” and “Watabukitsuneana2-chome” are “large damage”.

The first damage situation analysis model 126 is a machine learningmodel constructed by a method such as a neural network, a support vectormachine, or boosting. The first damage situation analysis model 126 isstored in the storage 85, is read out from the storage 85 by the RWcontrol unit 100, and is output to the first processing unit 121.

As an example, as shown in FIG. 11 , in a training phase, the firstdamage situation analysis model 126 is trained by being given trainingdata 130. The training data 130 is a set of a training compartment image123L and a correct first damage situation 127CA corresponding to thetraining compartment image 123L. The training compartment image 123L isobtained by inputting the first aerial image 25 of a certain area 20into the compartment image cutout unit 120. The correct first damagesituation 127CA is a result of actually discriminating the first damagesituation 127 of the compartment 135 appearing in the trainingcompartment image 123L by a qualified person such as a house damagecertified person.

In the training phase, the training compartment image 123L is input tothe first damage situation analysis model 126. The first damagesituation analysis model 126 outputs a training first damage situation127L to the training compartment image 123L. Loss calculation of thefirst damage situation analysis model 126 using a loss function isperformed based on the training first damage situation 127L and thecorrect first damage situation 127CA. Various coefficients of the firstdamage situation analysis model 126 are update-set according to a resultof the loss calculation, and the first damage situation analysis model126 is updated according to the update-setting.

In the training phase of the first damage situation analysis model 126,the series of processing of the input of the training compartment image123L into the first damage situation analysis model 126, the output ofthe training first damage situation 127L from the first damage situationanalysis model 126, the loss calculation, the update-setting, and theupdating of the first damage situation analysis model 126 are repeatedlyperformed while the training data 130 is being exchanged. The repetitionof the series of processing is ended in a case where discriminationaccuracy of the training first damage situation 127L for the correctfirst damage situation 127CA reaches a predetermined set level. Thefirst damage situation analysis model 126 in which the discriminationaccuracy reaches the set level is stored in the storage 85 and is usedby the first processing unit 121.

As an example, as shown in FIG. 12 , the second imaging rangedetermination unit 102 determines, as the second imaging range 136, animaging range including regions where damage is determined to berelatively large as a result of the analysis of the first damagesituation 127. In the present example, the regions where damage isdetermined to be relatively large are the compartments 135 such as “Fuji1-chome” and “Watabukitsuneana 2-chome” of which the first damagesituation 127 is determined to be “large damage” by the first damagesituation analysis model 126.

Here, a compartment 135_F1 of “Fuji 1-chome” and a compartment 135_W2 of“Watabukitsuneana 2-chome” are included in the flight range FR_1 incharge of the second drones 11A_1 and 11B_1 (see FIG. 13 ). In thiscase, the second imaging range determination unit 102 prepares secondimaging range information 71A_1 that registers longitudes and latitudesand azimuthal angles of a plurality of imaging points corresponding to aplurality of second imaging ranges 136_F1 that cover the compartment135_F1 of “Fuji 1-chome”. The second imaging range determination unit102 prepares second imaging range information 71B_1 that registerslongitudes and latitudes and azimuthal angles of a plurality of imagingpoints corresponding to a plurality of second imaging ranges 136_W2 thatcover the compartment 135_W2 of “Watabukitsuneana 2-chome”. For example,100 m shown in FIG. 3 is registered in the items of altitude of thepieces of second imaging range information 71A_1 and 71B_1.

The transmission control unit 103 transmits the second imaging rangeinformation 71A_1 which is information on the second imaging range136_F1 that covers the compartment 135_F1 of “Fuji 1-chome” to thesecond drone 11A_1. The transmission control unit 103 transmits thesecond imaging range information 71B_1 which is information on thesecond imaging range 136_W2 that covers the compartment 135_W2 of“Watabukitsuneana 2-chome” to the second drone 11B_1. As describedabove, the second imaging range determination unit 102 determines thesecond imaging range 136 for each of two second drones 11A_1 and 11B_1.

In FIG. 13 showing an example of a relationship between the compartment135 and the second imaging range 136, the flight controller 65 of thesecond drone 11A_1 causes the second drone 11A_1 to sequentially fly tothe imaging points of the compartment 135_F1 of “Fuji 1-chome” accordingto the second imaging range information 71A_1. The camera controller 66of the second drone 11A_1 captures the second imaging range 136_F1 atthe imaging points and captures a plurality of second aerial images 26.Similarly, the flight controller 65 of the second drone 11B_1 causes thesecond drone 11B_1 to sequentially fly to the imaging points of thecompartment 135_W2 of “Watabukitsuneana 2-chome” according to the secondimaging range information 71B_1. The camera controller 66 of the seconddrone 11B_1 captures the second imaging range 136_W2 at the imagingpoints and captures a plurality of second aerial images 26.

Here, the second imaging range 136 is a range that is relativelynarrower than the first imaging range 80, as can be seen in comparisonwith the first imaging range 80 shown in FIG. 7 . The second imagingrange 136 is a range having a size of, for example, ⅕ to 1/10 of thefirst imaging range 80.

As an example, as shown in FIG. 14 , the second damage situationanalysis unit 104 includes a building information assignment unit 140, abuilding image cutout unit 141, and a second processing unit 142. Thebuilding information assignment unit 140 assigns building information144 to each building appearing in the second aerial image 26 whilereferring to a building information assigned map 143, and uses thesecond aerial image 26 as a building information assigned second aerialimage 261. The building information assignment unit 140 outputs thebuilding information assigned second aerial image 261 to the buildingimage cutout unit 141.

The building information assigned map 143 is stored in the storage 85,is read out from the storage 85 by the RW control unit 100, and isoutput to the building information assignment unit 140. The buildinginformation assigned map 143 is a three-dimensional map of the area 20,and features points such as corners of a roof and the buildinginformation 144 are associated with each building. Specifically, thebuilding information 144 is a name of an owner of a building (house)such as “Fuji Kazuo” or a name of a building such as “Fuji Building 1”.The building information 144 also includes an address of the building.

The building information assignment unit 140 adjusts an orientation ofthe building on the building information assigned map 143 to anorientation of the building appearing in the second aerial image 26based on longitude and latitude, azimuth, and altitude of the seconddrone 11 in a case where the second aerial image 26 is captured, a tiltangle of the second camera 37, and the like. The building informationassignment unit 140 extracts feature points such as corners of a roof ofa building appearing in the second aerial image 26. The buildinginformation assignment unit 140 matches the building informationassigned map 143 and the second aerial image 26 according to theorientation of the building appearing in the second aerial image 26, andsearches for a position where a correlation between feature points ofthe building information assigned map 143 and feature points of thesecond aerial image 26 is highest. At the position where the correlationis highest, the building information 144 of the building informationassigned map 143 is added to each building of the second aerial image26.

The building image cutout unit 141 cuts out building images 145 from thebuilding information assigned second aerial image 261 by using, forexample, a machine learning model (not shown) using the aerial image asan input image and the image of each building appearing in the aerialimage as an output image. The building image cutout unit 141 outputs abuilding image group 146 including a plurality of sets of the buildingimage 145 and the building information 144 to the second processing unit142.

The second processing unit 142 inputs the building images 145 into asecond damage situation analysis model 147. The second damage situation148 is output from the second damage situation analysis model 147. Thesecond damage situation 148 assumes an earthquake or the like as thedisaster, and is any one of “completely destroyed”, “half destroyed”, or“safe”. The second processing unit 142 outputs the second damagesituation 148 from the second damage situation analysis model 147 forall the building images 145 included in the building image group 146.The second processing unit 142 outputs the second analysis result 111 inwhich the second damage situation 148 for each building is summarized.In FIG. 14 , a case where the second damage situations 148 of thebuildings of “Fuji Kazuo” and “Fuji Jiro” are “completely destroyed”,the second damage situation 148 of the building of “Fuji Mita” is “halfdestroyed”, and the second damage situation 148 of “Fuji Building 1” is“safe” is illustrated.

Similar to the first damage situation analysis model 126, the seconddamage situation analysis model 147 is a machine learning modelconstructed by a method such as a neural network, a support vectormachine, or boosting. The second damage situation analysis model 147 isstored in the storage 85, is read out from the storage 85 by the RWcontrol unit 100, and is output to the second processing unit 142.

As an example, as shown in FIG. 15 , in the training phase, the seconddamage situation analysis model 147 is trained by being given trainingdata 150. The training data 150 is a set of a training building image145L and a correct second damage situation 148CA corresponding to thetraining building image 145L. The training building image 145L isobtained by inputting the second aerial image 26 of a certain area 20into the building image cutout unit 141. The correct second damagesituation 148CA is a result of actually discriminating the second damagesituation 148 of the building appearing in the training building image145L by a qualified person such as a house damage certified person.

In the training phase, the training building image 145L is input to thesecond damage situation analysis model 147. The second damage situationanalysis model 147 outputs a training second damage situation 148L tothe training building image 145L. Loss calculation of the second damagesituation analysis model 147 using a loss function is performed based onthe training second damage situation 148L and the correct second damagesituation 148CA. Various coefficients of the second damage situationanalysis model 147 are update-set according to a result of the losscalculation, and the second damage situation analysis model 147 isupdated according to the update-setting.

In the training phase of the second damage situation analysis model 147,the series of processing of the input of the training building image145L into the second damage situation analysis model 147, the output ofthe training second damage situation 148L from the second damagesituation analysis model 147, the loss calculation, the update-setting,and the updating of the second damage situation analysis model 147 arerepeatedly performed while the training data 150 is being exchanged. Therepetition of the series of processing is ended in a case wherediscrimination accuracy of the training second damage situation 148L forthe correct second damage situation 148CA reaches a predetermined setlevel. The second damage situation analysis model 147 in which thediscrimination accuracy reaches the set level is stored in the storage85 and is used by the second processing unit 142.

As an example, as shown in FIG. 16 , the damage situation display screen112 displayed on the display 15 of the client terminal 14 has abuilding-specific damage situation display region 155 and a statisticaldamage situation display region 156. The building information 144, thebuilding image 145, and the second damage situation 148 of each buildingare displayed in the building-specific damage situation display region155. In the statistical damage situation display area 156, the totalnumber of each of completely destroyed, half destroyed, and safebuildings of the area 20 is displayed. In a case where a confirmationbutton 157 is selected, the display of the damage situation displayscreen 112 is erased. The building-specific damage situation displayregion 155 and/or the statistical damage situation display region 156may be displayed separately for each flight range FR or for eachcompartment 135.

Next, actions of the above configuration will be described withreference to the flowcharts of FIGS. 17 and 18 . First, in a case wherethe operation program 95 is started in the disaster informationprocessing server 12, as shown in FIG. 9 , the CPU 87 of the disasterinformation processing server 12 functions as the RW control unit 100,the first damage situation analysis unit 101, the second imaging rangedetermination unit 102, the transmission control unit 103, the seconddamage situation analysis unit 104, and the screen distribution controlunit 105. As shown in FIG. 10 , the first damage situation analysis unit101 includes the compartment image cutout unit 120 and the firstprocessing unit 121. As shown in FIG. 14 , the second damage situationanalysis unit 104 includes the building information assignment unit 140,the building image cutout unit 141, and the second processing unit 142.

In a case where the disaster occurs in the area 20, the first imagingrange 80 is captured by the first camera 36 mounted on the first drone10 as shown in FIG. 7 according to the first imaging range information70 shown in FIG. 6 , and as a result, the first aerial image 25 isobtained. The first aerial image 25 is transmitted from the first drone10 to the disaster information processing server 12.

As an example, as shown in FIG. 17 , in the disaster informationprocessing server 12, the first aerial image 25 from the first drone 10is received by the RW control unit 100 (step ST100). The first aerialimage 25 is stored in the storage 85 by the RW control unit 100.

The first aerial image 25 is read out from the storage 85 by the RWcontrol unit 100 and is output to the first damage situation analysisunit 101. As shown in FIG. 10 , the first damage situation 127 of thedisaster in the first imaging range 80 is analyzed by the first damagesituation analysis unit 101 based on the first aerial image 25 (stepST110). At this time, the first damage situation 127 is analyzed by thefirst damage situation analysis unit 101 for each compartment 135including the plurality of adjacent buildings. The analysis result ofthe first damage situation 127, that is, the first analysis result 110is output from the first damage situation analysis unit 101 to thesecond imaging range determination unit 102.

As shown in FIG. 12 , the second imaging range 136 of the second camera37 of the second drone 11 is determined by the second imaging rangedetermination unit 102 based on the first analysis result 110 (stepST120). At this time, the imaging range including the region wheredamage is determined to be relatively large as a result of the analysisof the first damage situation 127 is determined as the second imagingrange 136 by the second imaging range determination unit 102. The flightaltitude of the second drone 11 is set to be lower than the flightaltitude of the first drone 10 by the second imaging range determinationunit 102. The second imaging range 136 is determined by the secondimaging range determination unit 102 for each of the two second drones11.

The second imaging range information 71 which is the information on thesecond imaging range 136 is output from the second imaging rangedetermination unit 102 to the transmission control unit 103. The secondimaging range information 71 is transmitted to the second drone 11 bythe transmission control unit 103 (step ST130).

Subsequently, according to the second imaging range information 71, thesecond imaging range 136 is captured by the second camera 37 mounted onthe second drone 11 as shown in FIG. 13 , and as a result, the secondaerial image 26 is obtained. The second aerial image 26 is transmittedfrom the second drone 11 to the disaster information processing server12.

As an example, as shown in FIG. 18 , in the disaster informationprocessing server 12, the second aerial image 26 from the second drone11 is received by the RW control unit 100 (step ST200). The secondaerial image 26 is stored in the storage 85 by the RW control unit 100.

The second aerial image 26 is read out from the storage 85 by the RWcontrol unit 100 and is output to the second damage situation analysisunit 104. As shown in FIG. 14 , the second damage situation 148 of thedisaster in the second imaging range 136 is analyzed by the seconddamage situation analysis unit 104 based on the second aerial image 26(step ST210). The analysis result of the second damage situation 148,that is, the second analysis result 111 is output from the second damagesituation analysis unit 104 to the RW control unit 100 and is stored inthe storage 85 by the RW control unit 100.

In a case where the distribution request from the client terminal 14 isreceived, the second analysis result 111 is read out from the storage 85by the RW control unit 100 and is output to the screen distributioncontrol unit 105. The damage situation display screen 112 shown in FIG.16 is generated by the screen distribution control unit 105 based on thesecond analysis result 111. The screen data of the damage situationdisplay screen 112 is distributed to the client terminal 14 of adistribution request source by the screen distribution control unit 105(step ST220). The damage situation display screen 112 is displayed onthe display 15 of the client terminal 14 that is the distributionrequest source, and is used for viewing by the staff member of thedisaster response headquarters.

As described above, the CPU 87 of the disaster information processingserver 12 comprises the RW control unit 100, the first damage situationanalysis unit 101, and the second imaging range determination unit 102.The RW control unit 100 receives the first aerial image 25 obtained bycapturing the first imaging range 80 including the area 20 by the firstcamera 36 mounted on the first drone 10. The first damage situationanalysis unit 101 analyzes the first damage situation 127 of thedisaster in the first imaging range 80 based on the first aerial image25. The second imaging range determination unit 102 determines thesecond imaging range 136 of the second camera 37 mounted on the seconddrone 11 based on the first analysis result 110, and is the secondimaging range 136 relatively narrower than the first imaging range 80.

As described above, in the disclosed technology, first, the first damagesituation 127 which is a rough damage situation of the disaster isgrasped by the first aerial image 25 in which a relatively wide firstimaging range 80 appears. In light of the first damage situation 127,the second imaging range 136 for grasping the second damage situation148 which is a detailed damage situation of the disaster is determined.Accordingly, it is possible to grasp the damage situation at thedisaster site in a short time without waste as compared with a casewhere the plurality of drones are simply flown without any goal.

The second imaging range determination unit 102 determines, as thesecond imaging range 136, the imaging range including the region of thearea 20 in which damage is determined to be relatively large as a resultof the analysis of the first damage situation 127. There is apossibility that the region where damage is determined to be relativelylarge includes the disaster site. Thus, it is possible to moreefficiently grasp the damage situation at the disaster site.

The RW control unit 100 receives the second aerial image 26 obtained bycapturing the second imaging range 136 by the second camera 37 of thesecond drone 11. The second damage situation analysis unit 104 analyzesthe second damage situation 148 of the disaster in the second imagingrange 136 based on the second aerial image 26. Thus, it is possible toeasily grasp the second damage situation 148 which is more detailed thanthe first damage situation 127 without performing a complicatedinvestigation of actually walking around the disaster site.

The second imaging range determination unit 102 sets the flight altitudeof the second drone 11 to be lower than the flight altitude of the firstdrone 10. Thus, the performance of the second camera 37 is higher thanthe performance of the first camera 36, and the second aerial image 26which has a higher resolution than the resolution of the building of thefirst aerial image 25 and contributes to the analysis of the seconddamage situation 148 can be easily obtained without setting the zoommagnification of the second camera 37 to a telephoto side than the zoommagnification of the first camera 36.

The first damage situation analysis unit 101 analyzes the first damagesituation 127 for each compartment 135 including the plurality ofadjacent buildings. Thus, the analysis of the first damage situation 127can be completed in a shorter time than in a case where the analysis ofthe first damage situation 127 of each building is performed. As aresult, a dispatch timing of the second drone 11 can be advanced.

The plurality of second drones 11 are provided, and the second imagingrange determination unit 102 determines the second imaging range 136 foreach of the plurality of second drones 11. Thus, it is possible to graspthe damage situation at the disaster site in a shorter time than in thecase where the number of second drones 11 is one.

Instead of or in addition to setting the flight altitude of the seconddrone 11 to be lower than the flight altitude of the first drone 10, thesecond imaging range 136 may be relatively narrowed by setting the zoommagnification of the second camera 37 to the telephoto side than thezoom magnification of the first camera 36. Similar to the second damagesituation 148, the first damage situation 127 may be analyzed for eachbuilding. The number of second drones 11 in charge of one flight rangeFR may be one, or three or more.

Although any one of “large damage” or “small damage” is used as anexample of the first damage situation 127, the disclosed technology isnot limited thereto. The first damage situation 127 having three or morestages, such as any one of “extreme damage”, “medium damage”, or “smalldamage”, may be output. A degree of damage may be output as a numericalvalue of, for example, 1 to 10.

Second Embodiment

In the first embodiment, although the second damage situation 148 isanalyzed based only on the second aerial image 26, the disclosedtechnology is not limited thereto. As in a second embodiment shown inFIGS. 19 and 20 , the second damage situation may be analyzed based onthe first aerial image 25 in addition to the second aerial image 26.

As an example, as shown in FIG. 19 , the building information assignmentunit 161 of the second damage situation analysis unit 160 of the secondembodiment assigns the second building information 144 to each buildingappearing in the first aerial image 25 in addition to the second aerialimage 26 while referring to the building information assigned map 143,and uses the first aerial image 25 as a building information assignedfirst aerial image 251. A building image cutout unit 162 cuts out afirst building image 145A from the building information assigned firstaerial image 251 and cuts out a second building image 145B from thebuilding information assigned second aerial image 261. The secondbuilding image 145B is the same as the building image 145 of the firstembodiment. The building image cutout unit 162 outputs a first buildingimage group 146A including a plurality of sets of the first buildingimage 145A and the building information 144 and a second building imagegroup 146B including a plurality of sets of the second building image145B and the building information 144 to a second processing unit 163.

The second processing unit 163 inputs the first building image 145A andthe second building image 145B associated with the same buildinginformation 144 into a second damage situation analysis model 164. Asecond damage situation 165 is output from the second damage situationanalysis model 164. As in the case of the second damage situation 148 ofthe first embodiment, the second damage situation 165 is any one of“completely destroyed”, “half destroyed”, or “safe”. The secondprocessing unit 163 outputs the second damage situation 165 from thesecond damage situation analysis model 164 for all the first buildingimages 145A and the second building images 145B which are included inthe first building image group 146A and the second building image group146B and with which the same building information 144 is associated. Thefirst building image 145A and the second building image 145B with whichthe same building information 144 is not associated are input to thesecond damage situation analysis model 147 of the first embodiment andare output the second damage situation 148.

As an example, as shown in FIG. 20 , in the training phase, the seconddamage situation analysis model 164 is trained by being given trainingdata 170. The training data 170 is a set of a training first buildingimage 145AL, a training second building image 145BL, and a correctsecond damage situation 165CA corresponding to the training firstbuilding image 145AL and the training second building image 145BL. Thetraining first building image 145AL is obtained by inputting the firstaerial image 25 of a certain area 20 into the building image cutout unit162. The training second building image 145BL is obtained by inputtingthe second aerial image 26 of a certain area 20 into the building imagecutout unit 162. The correct second damage situation 165CA is a resultof actually discriminating the second damage situations 165 of thebuildings appearing in the training first building image 145AL and thetraining second building image 145BL by a qualified person such as ahouse damage certified person.

In the training phase, the training first building image 145AL and thetraining second building image 145BL are input to the second damagesituation analysis model 164. The second damage situation analysis model164 outputs a training second damage situation 165L to the trainingfirst building image 145AL and the training second building image 145BL.Loss calculation of the second damage situation analysis model 164 usinga loss function is performed based on the training second damagesituation 165L and the correct second damage situation 165CA. Variouscoefficients of the second damage situation analysis model 164 areupdate-set according to a result of the loss calculation, and the seconddamage situation analysis model 164 is updated according to theupdate-setting.

In the training phase of the second damage situation analysis model 164,the series of processing of the input of the training first buildingimage 145AL and the training second building image 145BL to the seconddamage situation analysis model 164, the output of the training seconddamage situation 165L from the second damage situation analysis model164, the loss calculation, the update-setting, and the updating of thesecond damage situation analysis model 164 are repeatedly performedwhile the training data 170 is being exchanged. The repetition of theseries of processing is ended in a case where discrimination accuracy ofthe training second damage situation 165L for the correct second damagesituation 165CA reaches a predetermined set level. The second damagesituation analysis model 164 in which the discrimination accuracyreaches the set level is stored in the storage 85 and is used by thesecond processing unit 163.

As described above, in the second embodiment, the second damagesituation analysis unit 160 analyzes the second damage situation 165based on the first aerial image 25 in addition to the second aerialimage 26. Since the building appears relatively small in the firstaerial image 25 than in the second aerial image 26, a resolution of thebuilding is inferior to a resolution in the second aerial image 26.However, in the first aerial image 25, the building appears at an angledifferent from an angle of the second aerial image 26, and it may beeasier to grasp the second damage situation 165 than in the secondaerial image 26. Thus, there is a high possibility that the seconddamage situation 165 of the building which is not clear only from thesecond aerial image 26 can be grasped, and as a result, reliability ofthe second analysis result 111 can be improved.

Third Embodiment

In a third embodiment shown in FIG. 21 , the second drone 11 is sent tosupport a region where damage of another flight range FR is determinedto be relatively large.

As an example, as shown in FIG. 21 , it is considered that the firstdamage situation analysis unit 101 analyzes that the first damagesituations 127 of compartments 135_1, 135_2, 135_3, and 135_4 are “largedamage” in the first flight range FR_1, whereas the first damagesituation analysis unit analyzes that there is no compartment 135 ofwhich the first damage situation 127 is “large damage” in the secondflight range FR_2. In this case, the second imaging range determinationunit 102 first determines, as the second imaging range 136 of the seconddrone 11A_1, a plurality of imaging ranges 136_1 that cover thecompartment 135_1. The second imaging range determination unit 102determines, as the second imaging range 136 of the second drone 11B_1, aplurality of imaging ranges 136_2 that cover the compartment 135_2.

The second imaging range determination unit 102 determines, as thesecond imaging range 136 of the second drone 11A_2 in charge of thesecond flight range FR_2, a plurality of imaging ranges 136_3 that coverthe compartment 135_3. The second imaging range determination unit 102determines, as the second imaging range 136 of the second drone 11B_2 incharge of the second flight range FR_2, a plurality of imaging ranges136_4 that cover the compartment 135_4. The second drones 11A_2 and11B_2 are examples of a “target second drone” according to the disclosedtechnology. The first flight range FR_1 is an example of “a flight rangedifferent from the flight range of the target second drone” according tothe disclosed technology, and the second flight range FR_2 is an exampleof “the flight range of the target second drone” according to thedisclosed technology. The compartments 135_3 and 135_4 are examples of“regions where damage is determined to be relatively large” according tothe disclosed technology.

As described above, in the third embodiment, in a case where there is aregion where damage in a region within the flight range FR of the targetsecond drone 11 is determined to be relatively small and damage isdetermined to be relatively large in a flight range FR different fromthe flight range FR of the target second drone 11 as a result of theanalysis of the first damage situation 127, the second imaging rangedetermination unit 102 determines, as the second imaging range 136 ofthe target second drone 11, an imaging range including the region wheredamage is determined to be relatively large. Thus, it is possible toeffectively utilize the second drone 11 having the flight range FR inwhich damage is determined to be relatively small. As a result, it ispossible to grasp the damage situation of the region where damage isdetermined to be relatively large in a shorter time. Not only the seconddrone 11 but also the first drone 10 may be sent to support.

It is preferable that a camera having high performance such as aresolution such that each building of the first aerial image 25 clearlyappears is used as the first camera 36. In contrast, the second camera37 may not have the same performance as the first camera 36.

The first aerial image 25 and the second aerial image 26 may betransmitted to the disaster information processing server 12 in a wiredmanner after the first drone 10 and the second drone 11 land on thedeparture and arrival base FB.

The flight range FR is not limited to the illustrated three locations.The flight range may be one location, two locations, or four or morelocations. A shape of the flight range FR is not limited to a circularshape. The shape of the flight range may be oval or rectangular.

The compartment 135 including the plurality of adjacent buildings is notlimited to the illustrated chome. A rectangular region having apredetermined size with a road as a boundary may be used as thecompartment 135.

In each of the above-described embodiments, although it has been assumedthat the first camera 36 and the second camera 37 are visible lightcameras, the disclosed technology is not limited thereto. As the firstcamera 36 and the second camera 37, an infrared camera may be preparedfor capturing in the evening or at night.

In each of the above-described embodiments, although any one of“completely destroyed”, “half destroyed”, or “safe” is used as anexample of the second damage situation on the assumption that anearthquake is mainly the disaster, the disclosed technology is notlimited thereto. Any one of “inundation above floor level”, “inundationunder floor level”, or “safe” may be output as the second damagesituation on the assumption that flood damage is the disaster. Any oneof “completely burned”, “half burned”, or “safe” may be output as thesecond damage situation on the assumption that large-scale fire is thedisaster. A second damage situation analysis model corresponding to atype of the disaster may be prepared, and the second damage situationanalysis model may be properly according to the type of the disaster.

In each of the above-described embodiments, for example, the followingvarious processors can be used as a hardware structure of processingunits that execute various kinds of processing such as the RW controlunit 100, the first damage situation analysis unit 101, the secondimaging range determination unit 102, the transmission control unit 103,the second damage situation analysis units 104 and 160, the screendistribution control unit 105, the compartment image cutout unit 120,the first processing unit 121, the building information assignment units140 and 161; the building image cutout units 141 and 162, and the secondprocessing units 142 and 163. As described above, in addition to the CPU87 which is a general-purpose processor that functions as variousprocessing units by executing software (operation program 95), thevarious processors include a programmable logic device (PLD), which is aprocessor capable of changing a circuit configuration after manufacture,such as a field programmable gate array (FPGA), and a dedicatedelectrical circuit, which is a processor having a circuit configurationspecifically designed in order to execute specific processing such as anapplication specific integrated circuit (ASIC).

One processing unit may be constituted by one of these variousprocessors, or may be constituted by a combination of two or moreprocessors of the same type or different types (for example, acombination of a plurality of FPGAs or a combination of a CPU and anFPGA). The plurality of processing units may be constituted by oneprocessor.

As an example in which the plurality of processing units are constitutedby one processor, firstly, one processor is constituted by a combinationof one or more CPUs and software as represented by computers such asclients and servers, and this processor functions as the plurality ofprocessing units. Secondly, a processor that realizes the functions ofthe entire system including the plurality of processing units via oneintegrated circuit (IC) chip is used as represented by a system on chip(SoC). As described above, the various processing units are constitutedby using one or more of the various processors as the hardwarestructure.

More specifically, an electric circuitry in which circuit elements suchas semiconductor elements are combined can be used as the hardwarestructure of these various processors.

The disclosed technology can also appropriately combine variousembodiments and/or various modification examples described above. Thedisclosed technology is not limited to the above embodiments, and mayadopt various configurations without departing from the gist. Forexample, in the present application, although the embodiments have beendescribed by using the multicopter type drone, the drone may be in theform of an airplane, a rotary-wing aircraft, a glider, an airship, orthe like as long as the drone is an unmanned aircraft.

The contents described and shown above are detailed descriptions for theportions related to the disclosed technology, and are merely examples ofthe disclosed technology. For example, the above description of theconfigurations, functions, actions, and effects is an example of theconfigurations, functions, actions, and effects of the portions of thedisclosed technology. Thus, the deletion of unnecessary portions, theaddition of new elements, or the substitution may be performed for thecontents described and shown above without departing from the gist ofthe disclosed technology. In order to avoid complications and facilitateunderstanding of the portions related to the disclosed technology, inthe contents described and shown above, common technical knowledge thatdoes not particularly require description is not described in order toenable the implementation of the disclosed technology.

In the present specification, “A and/or B” has the same meaning as “atleast one of A or B”. That is, “A and/or B” means that only A may beused, only B may be used, or a combination of A and B may be used. Inthe present specification, the same concept as “A and/or B” is alsoapplied to a case where three or more matters are expressed by “and/or”.

All the documents, patent applications, and technical standardsdescribed in the present specification are incorporated in the presentspecification by reference to the same extent as a case where individualdocuments, patent applications, and technical standards are specificallyand individually noted to be incorporated by reference.

What is claimed is:
 1. A disaster information processing apparatuscomprising: a processor; and a memory connected to or built in theprocessor, wherein the processor is configured to: receive a firstaerial image obtained by capturing a first imaging range including adisaster-stricken area by a first camera mounted on a first drone;analyze a first damage situation of a disaster in the first imagingrange based on the first aerial image; and determine a second imagingrange of a second camera mounted on a second drone based on an analysisresult of the first damage situation, the second imaging range beingrelatively narrower than the first imaging range.
 2. The disasterinformation processing apparatus according to claim 1, wherein theprocessor is configured to: determine, as the second imaging range, animaging range including a region where damage is determined to berelatively large as a result of the analysis of the first damagesituation in the disaster-stricken area.
 3. The disaster informationprocessing apparatus according to claim 1, wherein the processor isconfigured to: receive a second aerial image obtained by capturing thesecond imaging range by the second camera; and analyze a second damagesituation of the disaster in the second imaging range based on thesecond aerial image.
 4. The disaster information processing apparatusaccording to claim 3, wherein the processor is configured to: analyzethe second damage situation based on the first aerial image in additionto the second aerial image.
 5. The disaster information processingapparatus according to claim 1, wherein the processor is configured to:set flight altitude of the second drone to be lower than flight altitudeof the first drone.
 6. The disaster information processing apparatusaccording to claim 1, wherein the processor is configured to: analyzethe first damage situation for each compartment including a plurality ofadjacent buildings.
 7. The disaster information processing apparatusaccording to claim 1, wherein a flight range is set for the second dronein advance, and the processor is configured to: determine, as the secondimaging range of a target second drone, an imaging range including aregion where damage is determined to be relatively large in a case wheredamage of a region within the flight range of the target second drone isdetermined to be relatively small and there is a region where damage isdetermined to be relatively large in a flight range different from theflight range of the target second drone as a result of the analysis ofthe first damage situation.
 8. The disaster information processingapparatus according to claim 1, wherein a plurality of the second dronesare provided, and the processor is configured to: determine the secondimaging range for each of the plurality of second drones.
 9. Anoperation method of a disaster information processing apparatus,comprising: receiving a first aerial image obtained by capturing a firstimaging range including a disaster-stricken area by a first cameramounted on a first drone; analyzing a first damage situation of adisaster in the first imaging range based on the first aerial image; anddetermining a second imaging range of a second camera mounted on asecond drone based on an analysis result of the first damage situation,the second imaging range being relatively narrower than the firstimaging range.
 10. A non-transitory computer-readable storage mediumstoring an operation program of a disaster information processingapparatus causing a computer to execute processing of: receiving a firstaerial image obtained by capturing a first imaging range including adisaster-stricken area by a first camera mounted on a first drone;analyzing a first damage situation of a disaster in the first imagingrange based on the first aerial image; and determining a second imagingrange of a second camera mounted on a second drone based on an analysisresult of the first damage situation, the second imaging range beingrelatively narrower than the first imaging range.
 11. A disasterinformation processing system comprising: a first drone on which a firstcamera that captures a first imaging range including a disaster-strickenarea to output a first aerial image is mounted; a second drone on whicha second camera that captures a second imaging range relatively narrowerthan the first imaging range to output a second aerial image is mounted;a processor; and a memory connected to or built in the processor,wherein the processor is configured to: receive the first aerial image;analyze a first damage situation of a disaster in the first imagingrange based on the first aerial image; and determine the second imagingrange based on an analysis result of the first damage situation.